Effectiveness of Crowd-Sourcing On-Demand Assistance from Teachers in Online Learning Platforms
Effectiveness of Crowd-Sourcing On-Demand Assistance from Teachers in Online Learning Platforms
复制标题
在线学习平台中教师众包按需协助的有效性
DOI：
10.1145/3386527.3405912
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Heffernan, Neil T.
中科院分区：
文献类型：
--
作者：
Patikorn, Thanaporn;Heffernan, Neil T.
多项研究表明，专家创建的按需帮助（如提示信息）可以提高学生在在线学习环境中的学习效果。然而，也有证据表明，某些类型的援助可能不利于学生的学习。此外，创建和维护按需援助既困难又耗时。在2017-2018学年，132，738个不同的问题被分配到ASSISTments内部，但其中只有38，194个问题有按需援助。为了扩大按需援助的规模，我们需要一个能够收集新的按需援助并允许我们测试和衡量其有效性的系统。因此，我们在ASSISTments中设计并部署了TeacherASSIST。TeacherASSIST允许教师在将问题分配给学生时为任何问题创建按需帮助。然后，TeacherASSIST将一名教师按需提供的帮助重新分配给教室外的学生。我们发现，在三年内，ASSISTments内部的教师为25，957个不同的问题创造了40，292个新的援助实例。有14名教师创建了1 000多个按需援助实例。我们还进行了两个大规模的随机对照实验，以调查如何按需援助创建一个教师影响学生的课堂外。学生谁收到按需援助的一个问题导致下一个问题的性能显着的统计改善。学生在这个实验中的进步证实了我们的假设，即众包按需援助的质量足以提高学生的学习，使我们能够采取按需援助的规模。
It has been shown in multiple studies that expert-created on-demand assistance, such as hint messages, improves student learning in online learning environments. However, there are also evident that certain types of assistance may be detrimental to student learning. In addition, creating and maintaining on-demand assistance are hard and time-consuming. In 2017-2018 academic year, 132,738 distinct problems were assigned inside ASSISTments, but only 38,194 of those problems had on-demand assistance. In order to take on-demand assistance to scale, we needed a system that is able to gather new on-demand assistance and allows us to test and measure its effectiveness. Thus, we designed and deployed TeacherASSIST inside ASSISTments. TeacherASSIST allowed teachers to create on-demand assistance for any problems as they assigned those problems to their students. TeacherASSIST then redistributed on-demand assistance by one teacher to students outside of their classrooms. We found that teachers inside ASSISTments had created 40,292 new instances of assistance for 25,957 different problems in three years. There were 14 teachers who created more than 1,000 instances of on-demand assistance. We also conducted two large-scale randomized controlled experiments to investigate how on-demand assistance created by one teacher affected students outside of their classes. Students who received on-demand assistance for one problem resulted in significant statistical improvement on the next problem performance. The students' improvement in this experiment confirmed our hypothesis that crowd-sourced on-demand assistance was sufficient in quality to improve student learning, allowing us to take on-demand assistance to scale.
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